在元分析中P-hacking:正式化和新的元分析方法.
1Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California, USA.
Research synthesis methods
|January 25, 2024
概括
发表偏见可以发生在研究 (SAS) 或在研究 (SWS) 通过p-hacking. 新的方法分析非肯定的估计,以解决这两种选择类型,提高元分析的稳定性.
科学领域:
- 生物统计学 生物统计学
- 研究方法研究方法研究方法学
- 科学完整性 科学完整性
背景情况:
- 出版偏见,传统上被视为跨研究 (SAS) 选择,有利于发表显著的结果.
- 在研究中的选择 (SWS) 或p-hacking,即使在已公布的肯定结果中,也可以对估计产生偏见.
- 现有的元分析方法往往无法解释SAS和SWS的综合影响.
研究的目的:
- 开发用于元分析的新方法,解决跨研究 (SAS) 和研究 (SWS) 内的选择.
- 为评估元分析与联合出版偏见的稳定性提供工具.
- 在存在复杂选择偏差的情况下,提高元分析估计的准确性和可靠性.
主要方法:
- 提出了两种新的分析方法,专注于发表的非肯定的 (负面或不显著) 估计.
- 开发了"右截止元分析" (RTMA),通过归纳完整的影响分布来估计元分析平均值.
- 引入了"非肯定性研究的元分析" (MAN) 作为在减弱假设下的保守估计.
主要成果:
- 拟议的方法,RTMA和MAN,为处理联合SAS和SWS提供了互补的方法.
- 通过对人口效应的整个分布进行建模,RTMA提供了基础元分析平均值的估计.
- MAN产生了保守的,负偏差的估计,在更广泛的条件下提供了稳定性.
结论:
- 开发的方法和附带的R包 (拼接) 提高了检测和纠正复杂出版偏差的能力.
- 这些方法补充了现有的技术,提供了对元分析有效性的更全面的评估.
- 解决SAS和SWS的问题对于从综合研究中得出的强有力的科学结论至关重要.
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